This project is a comparative study of Autoencoder (AE) and Principal Component Analysis (PCA) for dimensionality reduction in gene expression data. It aims to understand the unique capabilities and applications of both methods in handling high-dimensional biological data.
machine-learning
bioinformatics
ae
pca
dimensionality-reduction
autoencoders
bioinformatics-tool
geneexpression
autoencodervspca
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Updated
May 25, 2024 - Jupyter Notebook